Purdue Agricultural Economics Report PURDUE AGRICULTURAL ECONOMICS REPORT YOUR SOURCE for IN-DEPTH AGRICULTURAL NEWS STRAIGHT from the EXPERTS

Home , Potential output

Purdue Agricultural Economics Report PURDUE AGRICULTURAL ECONOMICS REPORT YOUR SOURCE FOR IN-DEPTH AGRICULTURAL NEWS STRAIGHT FROM THE EXPERTS

JUNE 2019

CONTENTS Page Where’s the Inflation? 1

Indiana Farmland Values & Rents: Opinions from the Indiana Chapter of Farm Managers & Rural 8 Appraisers from February 2019

Comparing Crop Costs and Returns Across The Globe 10 Small Business Recovery Following a Natural Disaster? 14 Indiana Farm Management Tour: June 27-28 in Huntington and Wabash Counties 15 Corn Storage Returns: Implications for Storage and Pricing Decisions 16 A Closer Look at Recent Variability in On-Farm Corn Storage Returns 21 Soybean Storage Returns: Implications for Storage and Pricing Decisions 23

WHERE’S THE INFLATION?

LARRY DEBOER, PROFESSOR OF AGRICULTURAL ECONOMICS

The United States economy is at capacity, with an many machines available to run. Sometimes the unemployment rate near 50-year lows. In the past economy does so well that all of our resources are in such low unemployment resulted in rising inflation. use. The economy is at capacity. We’re producing at In our time, though, the inflation rate has remained “potential output.” near 2%. It has not increased. So, “Where’s the inflation?” Now, suppose we try to produce more anyway. Sup- pose spending by consumers, businesses or the gov- Why should we expect inflation? ernment increases beyond the economy’s potential output. Businesses see the opportunity and try to re- Resources are limited. There are only so many peo- spond by using resources that they would not ordi- ple available to work, so much land available to narily use. They plant crops on less productive land, plant, so many minerals available to mine and so or bring obsolete machinery back into production.

1 | Page Purdue Agricultural Economics Report They try to out-bid their competitors for land, miner- rate” of unemployment is the rate when the economy als or equipment. is at capacity. The natural rate of unemployment is usually thought to be in the neighborhood of 5 per- Businesses hire less qualified or inexperienced cent. It’s greater than zero because it takes time for workers that they would not ordinarily hire. They job seekers to find open jobs and employers with open tell their HR departments to make extraordinary ef- jobs to find job seekers. They will find each other, forts to find workers. They offer training, moving though, because at capacity there’s a job opening for expenses, or transportation. They raise wages and every employee. offer better benefits. They try to attract workers from competitors, or entice them out of school, re- Let’s measure inflation using the Consumer Price In- tirement or the home. dex without food and energy, to take out the fluctuations from food and oil prices. That’s called the “core” All of these efforts raise the costs of resources. Busi- inflation rate. Figure 1 shows the annual unemploy- nesses pass at least some of these higher costs to ment and core inflation rates. The solid red line is the their customers in higher prices. That’s inflation. unemployment rate, and the dotted blue line is the Inflation results when we try to produce beyond ca- core inflation rate. The gray bars mark recessions pacity. from beginning to end (peak to trough).

We can measure capacity with the unemployment When the unemployment rate rises, the inflation rate rate. The unemployment rate is the number of peo- tends to fall. You can mark those events with the gray ple without jobs but who are searching for work, as bars, which show the recessions. The core inflation a percentage of the labor force, which is the sum of rate fell during or immediately after every recession employed and unemployed people. The “natural since 1958.

Figure 1. Unemployment Rate and Core Inflation Rate, annual, 1958-2018

2 | Page Purdue Agricultural Economics Report

Expansions are the periods between recessions. The creased? Here are some possible reasons. unemployment rate falls during expansions. Inflation tends to rise, especially towards the end of expan- Maybe the “Phillips Curve” is dead? sions, when the unemployment rate gets low. “Phillips” was A.W. Phillips, a New Zealand-born Table 1 uses this same data on a monthly basis. It economist who famously plotted the relationship be- shows the level of the unemployment rate in the col- tween the unemployment rate and the inflation rate of umns, and the average change in the core inflation wages in 1958. The plot had a downward slope. Low- rate for different time periods in the rows. Core in- er unemployment made for higher wage increases. flation is measured as the percent change in the price Then the U.S. economy traced out a perfect Phillips index over the previous 12 months, and the averages relationship from 1961 to 1969 (Figure 2), plotted are multiplied by 12, to show what would happen if with price inflation instead of wage inflation. After the unemployment rate remained at a particular level that the Phillips Curve didn’t turn out to be so stable, for a year. but the downward slope remained.

Table 1. Average Change in Core Inflation over One Year, at Various Unemployment Rates (Monthly Data at Yearly Rates) Above 6% 6% or Less 5% or Less 4% or Less 1958-2019 -0.6% 0.4% 0.4% 0.9% 1958-1994 -0.8% 0.7% 0.9% 1.2% 1995-2007 -0.5% 0% 0% 0.4% 2008-2019 -0.1% 0% 0% 0.2%

Over the whole 1958-2019 period, when the unem- The data in Table 1 for 1958 through 1994 are evi- ployment rate was above 6%, the inflation rate went dence for the downward slope of the Phillips Curve. down. When the unemployment rate was below 6%, During those years unemployment rate above 6% the inflation rate went up. When the unemployment caused relatively large declines in inflation, and low- rate was below 4%, the inflation rate went up more. er unemployment rates caused increasing inflation, When labor is plentiful, prices rise more slowly; more-so when the unemployment rate was really low. when labor is scarce, prices rise more quickly. Infla- tion rises when the economy is above potential out- However, since 1995 there has been little response of put. inflation to low unemployment, except at the very lowest unemployment rates. Declines of inflation dur- The unemployment rate has been at or below 5% ing high unemployment have been less marked as since December 2015. That’s 40 months, 3 and one- well. The Phillips Curve has flattened. Maybe it’s third years. Based on the 62-year average, the core dead. Maybe the old relationship between unemploy- inflation rate should have increased 0.4% per year, ment and inflation is no more. from 2.1% in December 2015, to 3.4% in April 2019. Recent research suggests that the Phillips Curve isn’t dead, it’s just hibernating. Economists Hooper, Mish- Why has inflation remained low? kin and Sufi think that stabilizing policies by the Fed- eral Reserve have held inflation in check, masking But it didn’t. The 12-month core inflation rate was the underlying Phillips Curve inflation response to 2.1% in December 2015, and 2.0% in April 2019. unemployment. They examined state and local data The economy is at capacity or beyond, and inflation on inflation and unemployment, and found evidence has remained stable. Why has inflation not infor the downward slope.

3 | Page Purdue Agricultural Economics Report

Figure 2. Phillips Curve: Unemployment Rate and Core Inflation Rate, 1961-1969

If the Phillips Curve is alive and well, though, why Labor force participation is much lower now than it has low unemployment not caused rising inflation? was before the Great Recession of 2007-2009. It was 62.8% in April 2019. At the end of the last expansion, Maybe we’re not at capacity? in December 2007, it was 66.0%. There seem to be workers on the sidelines who could come back to There may be more employees available to hire, even work. with the unemployment rate at 3.6%. If so, businesses could find more employees without extraordinary and In December 2015, when the unemployment rate hit costly efforts, and without having to raise pay. There 5%, the labor force participation rate was 62.7%. The would be no higher costs to pass on in higher prices. rate has edged up by a tenth. That’s not enough to ex- Inflation would not increase. plain stable inflation.

Labor force participation measures the percentage of Besides, wages are rising faster. Average hourly earn- the employable population who are working or look- ings were increasing 2.5% per year in December ing for work. If more workers returned to the labor 2015. As of April 2019, they had risen 3.4% from a force and got jobs, the number of unemployed people year before. This is just what we’d expect if labor was would remain the same, but the labor force would in- scarce. A.W. Phillips’ original curve, which plotted crease. Since the unemployment rate is the number of unemployment with wage inflation, is alive and well. unemployed people as a percentage of the labor force, This is evidence that the economy is at capacity and the unemployment rate would go down. Lower unem- thus it does not explain why inflation has remained ployment would not be associated with higher infla- low. tion.

4 | Page Purdue Agricultural Economics Report

Figure 3. Productivity Growth. Percent Change in Real GDP per Employee, Annual Rate.

Maybe productivity is rising? rates from 1995 to 2019. Productivity growth averaged 2% per year from 1995 to 2006, but since then Labor is scarce and becoming more expensive. Busi- has averaged only 0.9% per year. In the past two-and- nesses might respond by adopting labor-saving tech- a-half years, however, productivity growth has been nology, to maintain or increase production with their increasing. As the unemployment rate dropped under existing employees. Automation would increase 5%, and wage growth increased, productivity also be- productivity, which is a rise in output per employee. gan to grow faster. So, rising productivity growth may With rising productivity businesses would not have be one reason why inflation has not increased. to raise prices to cover higher labor costs. Sales of added output would generate the needed revenue. Maybe profits are lower? Rising productivity would hold inflation down. Resource costs are rising. Businesses could hold infla- This happened in the second half of the 1990’s. Un- tion down if they are willing to take lower profits ra- employment was below 5%, wages were rising by ther than raise prices. 4% per year, but inflation continued to fall until late in the decade (Figure 1). The information technolo- One measure of profit margins is corporate profits be- gy revolution caused an increase in output per work- fore tax as a share of corporate value added, from the er. Wages rose more rapidly, but inflation remained Gross Domestic Product accounts. It fell from 2014 to low. 2015, but since then has remained relatively stable. Profits do not appear to have dropped since unem- Figure 3 shows the percentage change in real gross ployment fell below 5% and wage growth picked up. domestic product per employee, quarterly at annual But, profits after taxes rose considerably after the De- cember 2017 tax cut, however.

5 | Page Purdue Agricultural Economics Report

Maybe imports are up? As of 2019 inflation has been low and stable for a long time. Annual core inflation rates have been with- Imported goods compete with domestically pro- in one percentage point of 2% in all but one year since duced goods. If the prices of domestic goods began 1996, a two decade run of stable inflation. As a result, to rise, perhaps businesses and consumers would people expect stable inflation to continue at a rate near turn to less expensive imported goods. Consumers 2% per year. would pay lower prices, both because imports themselves were cheaper, and because import competi- Inflationary expectations can be measured by compar- tion would discourage domestic businesses from ing the Treasury bond yields to inflation-indexed raising prices. Either way, inflation would be lower. Treasury bond yields. The difference between the two is the inflation rate that bond holders expect. Expected Imports as a share of GDP grew rapidly during the inflation has varied within seven-tenths of 2% every 1990’s and 2000’s. Perhaps this contributed to the month since the end of the recession. low inflation after the mid-1990’s. But imports were 14.9% of GDP in the fourth quarter of 2015, and are The University of Michigan surveys consumers about 14.9% in the first quarter of 2019. Imports have not their expectations every month. This measure shows risen above the overall growth rate since the unem- more variation, but expected inflation was 2.6% in ployment rate dropped below 5%. December 2015, and 2.5% in March 2019.

Imports are affected by trade disputes and tariffs. There is no evidence that people are expecting higher Prices of domestic goods may play a small part in inflation with the economy at capacity. This elimi- fluctuations of trade. Still, there’s no evidence in nates a possible source of inflation. these numbers that rising imports have held inflation down in recent years.

Maybe it’s stable inflationary expectations?

The Federal Open Market Committee’s policy statement usually includes a phrase like this one from May 1, 2019:

On balance, market-based measures of inflation compensation have remained low in recent months, and survey-based measures of longer-term inflation expectations are little changed.

Concern about inflationary expectations goes back to the “wage-price spiral” of the 1970’s. Businesses OK, Why Does Inflation Matter? anticipated that inflation would raise costs, so they raised their prices. Workers and other resource sup- It matters to the Federal Reserve. The Federal Reserve pliers anticipated higher prices, so they raised their has a dual mission, to keep inflation and unemploy- wage and resource costs. Everyone’s expectations ment low. The Fed’s inflation target is 2%. If they were confirmed. Business costs did rise, consumer expect inflation to rise much above 2%, they will act prices rose too. Expectations of inflation continued, to restrain borrowing and spending by raising interest and were themselves a cause of actual inflation. rates. Since it takes 6 months to a year for higher interest rates to slow the economy, they must act in ad-

6 | Page Purdue Agricultural Economics Report vance. They need to know when to anticipate rising References: inflation. Appelbaum, Binyamin. “Fed Signals End of Interest Rate Increases,” The New York Times, January 30, The Fed estimates the natural rate of unemployment 2019. for this reason. If the actual unemployment rate falls below the natural rate, then rising inflation is to be Bernstein, Jered. “Why would the Fed want to raise expected, and interest rates should be raised. The the unemployment rate a full percentage point?” The Fed’s estimate of the natural rate was 4.5% in mid- Washington Post, June 18, 2018. 2018 (Bernstein). The unemployment rate is now Federal Reserve Press Release, May 1 2019. well below that rate, and inflation has not increased. www.federalreserve.gov/monetarypolicy/ In an April 22, 2019 interview with the Wall Street fomccalendars.htm Journal, Chicago Federal Reserve Bank president Hooper, Peter, Frederic S. Mishkin, Amir Sufi, Charles Evans said the low inflation made him “Prospects for Inflation in a High Pressure Economy: “wonder if the natural rate of unemployment might Is the Phillips Curve Dead or is It Just Hibernating?” be even lower than my current assessment of 4.3%. NBER Working Paper No. 25792, May 2019 At 3.8%, we’re running just a little bit below that but it’s not causing any difficulties.” Since inflation has Ip, Greg. “Looking for Mr. Phillips,” The Wall Street not appeared, Fed officials appear to be reducing Journal, May 3, 2019. Reporter Greg Ip plots the Phil- their estimates of the natural rate. lips Curve with wage inflation on the vertical axis, 2009-19. The curve slopes downward. During the low unemployment in the second half of “Transcript: WSJ Interview with Chicago Fed Presi- the 1990’s, Alan Greenspan’s Fed famously did not dent Charles Evans,” The Wall Street Journal, April increase interest rates as unemployment fell. They 22, 2019. gambled that more rapid productivity growth would keep inflation low. It did. Data are from the Federal Reserve Economic Data (FRED) website, fred.stlouisfed.org. Now the Fed appears willing to make a similar gam- ble. Unemployment is 3.6%, below any estimate of the natural rate of unemployment. Chairman Powell has said that the Fed does not intend to increase interest rates in 2019.

If productivity growth and stable inflationary expectations hold inflation down despite low unemployment and rising wages, we’re right to keep interest rates low. We can have low unemployment and low inflation at the same time. But if we’re wrong, and low unemployment does cause rising inflation, we may need higher interest rates and much slower growth to bring it down.

7 | Page Purdue Agricultural Economics Report INDIANA FARMLAND VALUES & RENTS: OPINIONS FROM THE INDIANA CHAPTER OF FARM MANAGERS & RURAL APPRAISERS FROM FEBRUARY 2019 1

CRAIG DOBBINS, PROFESSOR OF AGRICULTURAL ECONOMICS

In the upcoming August issue of this publication I Where are Farmland Values Headed? plan to release the results of our 2019 Indiana Responses from people representing 19 different Farmland and Cash Rent Survey. Here I am provid- counties were received. The average estimated price ing summaries from the Chicago Fed and a Febru- of farmland was $8,225 per acre. Fifty-three percent ary 2019 survey of Indiana Farm Managers and Ru- of the respondents indicated no change in farmland ral Appraisers. values when compared to values in February 2018. In the January 2019 issue of the AgLetter, the Fed- Sixteen percent of the respondents indicated the esti- eral Reserve Bank of Chicago reported District mated price was higher by an average of 7% com- farmland values remained the same from January 1, pared to the value in February 2018. Thirty-two per- 2018 to January 1, 2019. The most recent May cent indicated the estimated price was lower by an 2019 issue reported only a 1% increase from April average of 4% compared to the value in February 1, 2018 to April 1, 2019. For the last quarter of 2018. The overall average percentage change in farm- 2018, Indiana farmland values increased 3%. For land values for the year were 0.7%. This “no change” the first quarter of 2019, an increase of 2% was re- result for the year is consistent with the Chicago Fed- ported. These two increases were the largest quar- eral Reserve surveys for the last quarter of 2018 and terly increases in a District containing Iowa, Illi- the first quarter of 2019. nois, and parts of Indiana, Michigan, and Wiscon- sin. These data seem to indicate continued strength in Indiana farmland values. To ascertain if Indiana’s professional farm managers and rural appraisers held a similar view of Indi- ana’s farmland market, members of the Indiana Chapter of Farm Managers & Rural Appraisers were surveyed during their winter meeting on Feb- ruary 6, 2019. Members were asked questions about the current and expected future market values for the following farmland: The group was asked to provide two forecasts of fu- “80 acres or more, all tillable, no buildings, capa- ture farmland values. One was farmland values in one ble of averaging 195 bushels of corn per year and year. The second was farmland values in five years. 60 bushels of soybeans in a corn/bean rotation un- When asked about land values in one year, 42% of the der typical management and not having special non respondents indicated that values would be the same. -farm uses.” Twenty-one percent indicated farmland values would

______

1A special thanks is expressed to the Indianan Chapter of Farm Managers and Rural Appraisers that participated in the survey. The Indiana Chapter of Farm Manag- ers and Rural Appraisers is an organization of rural land experts located in Indiana and promotes the professions of farm management, agricultural consulting, and rural appraisal. Without their assistance it would not be possible to take the pulse of Indiana’s farmland market.

8 | Page Purdue Agricultural Economics Report be up an average of 3%. The remaining 37% indicat- period of one or two years. ed a decline in farmland values averaging 3.7%. Final Thoughts Across all responses, the expected change in farmland values for the coming year was -0.7%. In the These results indicate Indiana’s farmland market has short run, these respondents had a strong consensus been in a period of relative stability. While markets that farmland values will not increase. are seldom perfectly stable, these February expectations are for relatively small future changes at least by However, there was optimism for an increase in historical standards. But there are lots of uncertainties farmland values over the next five years. In this that could change these expectations. Tariffs and trade case, 83% of the respondents indicated farmland val- uncertainty remain highly uncertain. The U.S. agricul- ues would be higher by an average of 10%. Six per- tural economy is heavily dependent on exports. If the cent of the respondents expect farmland values to the ultimate result is lower commodity prices for farmers, same in five years and 11% expect farmland values as many seem to expect, this means lower margins to decline by an average of 7.5%. Across all re- and increased downward pressure on farmland values sponses, farmland values are expected to increase by and cash rents. The size of future grain price declines 7.3%. A 7.3% to 10% increase over five years is and the size of government payments provided to off- modest by historical standards. set price declines will be important influences in Indi- Cash Rents Not Much Change ana’s future farmland and cash rent market. Attendees were also asked to specify the cash rent Look for our 2019 Indiana Farmland and Rents Sur- for 2019. The average cash rent for the example par- vey results in this publication in early August. cel was estimated to be $238 per acre. The estimated cash rents varied from $115 to $300 per acre, a difference of $185 per acre. Eighty-four percent of the respondents indicated cash rent remained the same as in 2018. Five percent of the respondents indicated cash rents had risen and 11% indicated cash rents declined between 2018 and 2019. As with farmland values, the respondents were asked to forecast cash rents one-year and five-years into the future. When asked what cash rent would be in 2019, 72% of the respondents indicated they would be the same as 2018. Eleven percent expect cash rents to increase and 20% expected them to decline. The overall average change in cash rents was 0.7%, almost no change There was a little less agreement about the five-year projection. A majority of 63% of the respondents indicated cash rents would exceed the 2019 level by an average of 8.5%. Thirteen percent thought cash rents would be the same and 24% thought cash rents would be lower by an average of 5.5%. While there is a strong expectation cash rents will change, the amount of change, both up and down, is small. His- torically it is common for changes of the magnitude expected here over five years to be associated with a

9 | Page Purdue Agricultural Economics Report

COMPARING CROP COSTS AND RETURNS ACROSS THE GLOBE

RACHEL PURDY, PH.D. CANDIDATE AND RESEARCH ASSOCIATE MICHAEL LANGEMEIER, PROFESSOR OF AG. ECONOMICS, ASSOC. DIR. CENTER FOR COMMERCIAL AGRICULTURE

Examining the competitiveness of crop production Eight farms in the dataset produced corn, soybeans, in different regions of the world is difficult due to and wheat every year between 2013 and 2017. These lack of comparable data and agreement regarding farms are listed in Table 1 and are typical farms used what needs to be measured. To be useful, interna- in the agri benchmark network. Two of the eight tional data needs to be expressed in common pro- farms are from the United States (a southern Indiana duction units and converted to a common currency. farm and a North Dakota farm). Purdy (2019) pro- Also, production and cost measures need to be con- vides a more detailed analysis of international crop sistently defined across production regions. production using agri benchmark data.

This paper examines the competitiveness of crop Due to differences in technology adoption, input production from 2013 to 2017 using data from the prices, land fertility levels, efficiency of farm opera- agri benchmark network. The agri benchmark net- tors, trade policy restrictions, exchange rate effects, work collects data on beef, cash crops, dairy, pigs and labor and capital market constraints input use and poultry, horticulture, and organic products. varies across farms. In addition to presenting infor- There are 40 countries represented in the cash crop mation pertaining to gross revenue and cost per ton, network. The agri benchmark concept of typical this paper discusses input cost shares. farms was developed to understand and compare current farm production systems around the world. Costs were broken down into three major categories: Participant countries follow a standard procedure to direct costs, operating costs, and overhead costs. Di- create typical farms that are representative of nation- rect costs included seed, fertilizer, crop protection, al farm output shares and categorized by production crop insurance, and interest on these cost items. Op- systems or a combination of enterprises and structur- erating cost included labor, machinery depreciation al features. and interest, fuel, and repairs. Overhead cost includ-

Table 1: Typical Farms, Size, and Location Country Hectares Region Argentina 300 North Buenos Aires Argentina 700 South East of Buenos Aires Argentina 900 West of Buenos Aires Brazil 65 Parana, Cascavel Romania 6500 Lalomitia county, S.E. Romania United States (Southern Indiana) 1215 Southern Indiana United States (North Dakota) 1300 Barnes County, North Dakota South Africa 1600 Eastern Free State

10 | Page Purdue Agricultural Economics Report

Figure 1. Average Gross Revenue and Cost for Corn ($ per ton) ed land, building depreciation and interest, property cost share for average direct cost, at 52.2%. The Ro- taxes, general insurance, and miscellaneous cost. manian farm had the lowest cost share for average direct cost at 32.5%. Operating cost shares ranged from Corn: Argentina Farms Had Low Costs 21.0% on the smallest Argentinian farm to 42.0% on the Romanian farm. Overhead costs ranged from Figure 1 presents average gross revenue and cost per 17.2% on the South African farm to 39.9% on the ton for each typical farm for the 2013 to 2017 peri- smallest Argentinian farm. The average cost shares for od. Gross revenue and cost are reported in U.S. dol- the southern Indiana farm were 48.0%, 25.1%, and lars for each typical farm. Gross revenue was highest 26.9% for direct, operating, and overhead costs, re- for the South African farm, and lowest for the large spectively. Argentinian farm ($178 and $103 per ton, respectively). Gross revenue and cost per ton for the south- Soybeans: U.S. Farms had Positive Margins ern Indiana farm were $158 and $163 per ton, resulting in an economic loss of $5 per ton. Figure 2 presents average gross revenue and cost per ton for each typical farm. Gross revenue and cost are The typical farms from South Africa and Argentina reported as U.S. dollars per ton. Total cost of soybean exhibited economic profits during the five-year peri- production was lowest for the typical farms in Argen- od, earning an average of $20 per ton. Average loss- tina, and highest for the South African farm. Gross es for the remaining typical farms were $27 per ton, revenue and cost per ton for the southern Indiana farm during the five-year period. On average, economic were $385 and $368 per ton, resulting in an economic loss per ton was $3 per ton. profit of $17 per ton. The Brazilian and South African farms did not earn an economic profit producing soy- The average input cost shares were 42.8% for direct beans during the 2013 to 2017 period. Losses per ton cost, 29.9% for operating cost, and 27.3 % for over- were $13 per ton for the Brazilian farm and $139 per head cost. The North Dakota farm had the largest ton for the South African farm. On average, economic

11 | Page Purdue Agricultural Economics Report

Figure 2. Average Gross Revenue and Cost for Soybeans ($ per ton) profit was less than $1 per ton for the eight farms was highest on the Brazilian typical farm. The Brazili- examined in this study. an typical farm also had the highest economic loss during this time period, at $220 per ton. The average input cost shares were 28.6% for direct cost, 37.0% for operating cost, and 34.3% for over- The only typical farm in this sample to earn a positive head cost. The North Dakota farm had the highest economic profit in wheat production was the North cost share for direct costs, at 39.6%. The smallest Dakota farm, earning less than $1 per ton over the five Argentinian farm had the lowest cost share for direct -year period. The average economic loss was $55 per costs at 20.9%. Operating costs ranged from 22.9% ton for the eight farms in the sample. Given that the on the Southern Indiana farm to 58.8% on the South average gross revenue was only $175 per ton, the av- African farm. Overhead costs ranged from 14.2% on erage loss for the eight farms included in this paper the South African farm to 51.3% on the smallest Ar- was extremely large. Many of the primary wheat pro- gentinian farm. The average cost shares for the ducing countries were not included in this paper. For southern Indiana farm were 38.1%, 22.9%, and more information pertaining to the efficiency of typi- 39.0% for direct, operating, and overhead costs, re- cal farms with wheat from Australia, Canada, the Eu- spectively. ropean Union, Ukraine, and Russia see Purdy (2019).

Wheat: Wide Differences by Country The average input cost shares were 35.5% for direct cost, 31.8% for operating cost, and 32.7% for over- Figure 3 presents average gross revenue and cost per head cost. Average direct cost share ranged from ton for each typical farm. Gross revenue and cost are 26.0% on the Romanian farm to 46.9% on Argentina reported as U.S. dollars per ton. Wheat was a minor 700. The southern Indiana farm had the lowest operat- enterprise for the southern Indiana farm. The prima- ing cost share, at 18.2%. The South African farm had ry reason for growing wheat on this farm was to fa- the highest operating cost share at 56.0%. Due to rela- cilitate the production of double-crop soybeans. The tively high land costs, the southern Indiana farm had total cost of wheat production, on a per ton basis, the highest overhead cost share at 45.3%. The lowest

12 | Page Purdue Agricultural Economics Report

Figure 3. Average Gross Revenue and Cost for Wheat ($ per ton) overhead cost share was 17.3% on the South African corn, soybean, and wheat production during the 2013 farm. to 2017 period. Of the farms that had corn, soybeans, and wheat, the farms in Argentina and the United Conclusions States tended to have the highest levels of cost efficiency. In terms of just corn and soybeans, the farms This paper examined gross revenue and cost for in Argentina, Brazil, and the United States tended to eight corn, soybean, and wheat producing farms in have the highest levels of efficiency. the agri benchmark network from Argentina, Brazil, Romania, the United States, and South Africa for the References: years 2013 to 2017. The average economic profit Agri benchmark. http://www.agribenchmark.org/ was -$3, $0, and -$55 per ton for corn, soybeans, and home.html. Retrieved on 5/1/19. wheat, respectively. The range of economic profits was highest for wheat production ($221 per ton, Purdy, R. (2019). A Cost Efficiency Comparison of compared to $184 per ton for soybeans and $107 per International Corn, Soybean, and Wheat Production. ton for corn). Only one of the wheat farms and four Available from Dissertations & Theses @ CIC Institu- of the corn farms exhibited a positive economic tions; ProQuest Dissertations & Theses Global. profit over the study period. In contrast, six of the soybean farms had a positive economic profit.

In addition to examining gross revenue and cost per ton, Purdy (2019) examined the cost efficiency of

13 | Page Purdue Agricultural Economics Report

SMALL BUSINESS RECOVERY FOLLOWING A NATURAL DISASTER?

RENEE WIATT, FAMILY BUSINESS MANAGEMENT SPECIALIST, PURDUE INITIATIVE FOR FAMILY FIRMS MARIA I MARSHALL, PROFESSOR OF AG. ECONOMICS, & DIRECTOR, PURDUE INITITATIVE FOR FAMILY FIRMS

Small businesses may sometime face extremely dif- defined as firms that actually grew revenues after the ficult situations that can jeopardize survival. In this disaster compared to pre-storm levels. Small business- article we report on some of the characteristics of es were more likely to be resilient after Katrina if they firms that have survived a natural disaster. The in- had adjusted their insurance policy elections post- tent is to illustrate management decisions that can Katrina. These adjustments would assure that the busi- assistant any business in getting through the trauma. ness would be better protected in the event of another disruption. Some of the businesses that experienced After a disaster strikes, insurance is often the first Katrina were unlucky enough to be hit with an oil spill way to obtain funds for recovery costs. Businesses or Hurricane Isaac less than ten years following Katri- can buy a variety of insurance policies. Policies can na. Other factors that had a positive impact on resili- include flood insurance, business interruption insur- ency included: having a formal legal structure (i.e. ance, business recovery insurance, casualty and corporation or partnership), being married, being property insurance, and other policies specific to the male, and having a larger number of employees. businesses’ needs like inventory insurance. For home-based business, there is also coverage for homeowner insurance including flood insurance, property and casualty insurance.

For this case study, we investigated small businesses in a 10-county area in southeastern Mississippi after Hurricane Katrina in 2005. Of the 347 businesses in this area that survived Katrina, roughly 46% sustained major damage during the hurricane. Of the 116 businesses that closed since Katrina, roughly 63% sustained major damage during the storm.

Results from our research show that small businesses were more likely be operational if the business had property insurance in place before the disaster. Those businesses who sustained major damage from Hurricane Katrina were more likely to go out of business. Although damage from a natural disaster Also, businesses were more likely to achieve higher is unavoidable, having insurance in place is within a success after Hurricane Katrina if they owned the business owner’s control. Other factors that tended property where the business operated and had property to have a positive association with business survival insurance in effect before Katrina. after the storm included: have been in business for a longer period of time, having a male owner, an own- Businesses were less likely to have higher perceived er with a postsecondary education, and having a success after Katrina if insurance was unaffordable larger number of employees. after the natural disaster. Unfortunately, about 25% of small business owners could not get affordable insur- We also examined business “resilience” which we ance coverage following Hurricane Katrina. Being

14 | Page Purdue Agricultural Economics Report married and having more education were also posi- demise for a small business. tively related to business resiliency. But, older businesses were less likely to experience higher per- References: ceived success after Katrina. Marshall, M.I. and Schrank, H.L. (2014). Small business disaster recovery: a research framework. Natural The goal for small business owners should be to Hazards, 72, 597-616. DOI: 10.1007/s11069-013- have the correct safeguards in place to be able to sur- 1025-z. vive a disaster, to adapt and recover, and to come out other side even better than before. We call this being Acknowledgement: resilient. Insurance is not the only step that should be This article is based upon material from the Purdue University taken to protect small businesses, but it is an im- Project “Small Business Survival and Demise after a Natural Disaster”, supported by NSF Grant #0856221-CMMI and “Small portant one. Having the correct insurance coverage Business Disaster Recovery Process: An Analysis of Rural Com- in place can be the difference between survival and munities in Mississippi” supported by USDA-NIFA grant # 2011 -67023-30609.

Learn about innovative management strategies, new technologies for improving efficiency and productivity, and ways to help ensure a successful transition of the family farm to the next generation, at the 87th Annual Purdue Farm Manage- ment Tour, June 27-28. Purdue’s Center for Commercial Agriculture and Purdue Extension sponsor the tour, which includes stops at four farms in Huntington and Wabash counties. Farms are chosen based on their successful business management practices or unique perspective on farm business management. “This two-day event is a great opportunity for farmers to learn directly from the experiences of Indiana's best farm business managers and apply those principles to their own farms,” said James Mintert, director of Purdue University’s Cen- ter for Commercial Agriculture. Each tour includes an interview session where farm operators provide an overview of the farm, followed by three mini- tour sessions focusing on specific aspects of the farm’s operation. During the mini-sessions, host farmers share successful farm management tips and explain how the management of their operations is changing in response to the agricultural economy and evolving family circumstances. They also share reasons behind recent innovations in production practices and adoption of new technology. The tour is free and open to the public but registration is required by June 15 at purdue.edu/farmtour or by calling 765- 494-7004.

15 | Page Purdue Agricultural Economics Report CORN STORAGE RETURNS: IMPLICATIONS FOR STORAGE AND PRICING DECISIONS

CHRIS HURT, PROFESSOR OF AGRICULTURAL ECONOMICS

Grain storage is an important marketing function that est rates has changed over the 30 years in this study so provides “time value” to the grain. Grain production prior to the 2001 crop, the 6 month certificate of de- occurs at harvest time, but usage is spread through- posit interest rate was used. Starting with the 2001 out the marketing year. Thus storage is required to crop the prime interest rate was used. Individual farm- remove the harvest surplus and then to allocate that ers may use considerably different interest rates in surplus to users in an orderly manner until the next their personal storage decisions. harvest. For on-farm storage, if the cash bid rises by enough to Corn producers want to know how much return they cover the interest cost after harvest, then there was a might get from storing corn and when is the best positive return for that week. Of course those who time to price corn to give the highest storage returns. have on-farm storage know there are substantial costs To examine these important questions we look at the to owning and operating those facilities. Since the on- historical storage returns based on cash bids each farm returns in this study only consider interest as a week at a central Indiana unit-train loading facility. cost, this means that the returns reported here repre- These weekly cash bids are the Wednesday (mid- sent the $ per bushel left to cover ownership and oper- week) closing bid quoted publically by the facility ating costs for the on-farm storage.

First, we will explain how on-farm corn storage re- Returns in three time periods are reported. Those are: turns are estimated and then move on to commercial the most recent 10 crop years representing the corn storage returns. On-farm storage is the largest por- crops harvested in 2008 to 2017. Those are the tion of the state’s grain storage. USDA reports that 2008/2009 to 2017/2018 marketing years. Note that at 61% of the total storage space in Indiana is on-farm the time of this publication, the 2018/2019 marketing storage (see USDA: Grain Stocks report for Decem- year was not complete and thus is not included. The ber 1 data). The remaining 39% is off-farm storage at second time period is the most recent 20 years repre- locations like grain elevators, processing plants, senting the crops from 1998 to 2017; and a 30 period warehouses, and terminals that store grain for their for crops harvested in 1988 to 2017. own use and/or for a storage fee for customers.

For this study we assume the farmer puts the grain in the bin at harvest and takes the cash price bid the week they decide to price and deliver the grain. They are speculating on the cash price. Of course they hope the cash bid goes up after harvest by enough to give positive returns. The corn harvest value was assumed to be the average cash bid for the last-two weeks of October.

For on-farm storage, only weekly interest costs are subtracted as a cost of storage. The structure of inter-

16 | Page Purdue Agricultural Economics Report

Figure 1: Corn-Speculative Returns to On-Farm Storage Above Interest Cost by Week ($/Bu.)

Returns to Speculative On-Farm Corn Storage primarily the seasonal cash price pattern that has a tendency to reach peaks (on average over a series of Figure 1 shows returns to on-farm storage above in- years) in the spring. Cash prices have a tendency to terest cost by week in $ per bushel. The horizontal decline into the summer, especially the mid-to-late scale is weekly. Remember, harvest is the last two summer and accumulating interest costs also contrib- weeks of October so the storage returns begin in No- ute somewhat to lower summer storage returns. vember and run through the following August. The numbers 1-2-3-4 represent the weeks of each month. How much return has there been to cover the costs of These are the estimated returns per bushel available ownership and operating costs for on-farm corn stor- to cover the ownership and operating costs of on- age above interest costs? Over the long run, that has farm storage as defined by the assumptions in this been in the range of $.25 to $.40 per bushel when study. Remember they are averages of weekly re- viewed as simply taking the cash price offered each turns for the multiple years in each of the periods. week (speculative returns) and pricing in the near optimum time periods in late-February and early-March or For the three time periods note the consistent season- late-May and early-June. Also recognize that the as- al pattern of these returns throughout the storage sea- sumptions in this study may not be accurate for an in- son. Returns tend to rise from harvest into early- dividual situation. March. Then weaken in later-March and April, before peaking in May and early-June. Finally note the Average returns in the most recent period representing rapid decline in storage returns into the late-spring the 2008 to 2017 crops have been lower than the long- and summer. er periods. Does this say that returns to speculative corn storage are decreasing over time? My answer What drives this seasonal pattern of returns? It is would be No! When we look at returns in this manner the overall multi-year trends in prices over time can

17 | Page Purdue Agricultural Economics Report

Figure 2: Corn-Historical Odds of a Positive On-Farm Storage Return Above Interest Cost by Week have a big impact on these storage returns. As an When speculating for higher prices to give a positive example, if prices are overall going up, like during return to storage there can be a wide range of out- the ethanol build-up this tends to make storage re- comes primarily driven by the forces of supply and turns look strong as prices overall are rising. demand that determine prices. Harmful weather in South America can increase Indiana corn prices in our The opposite has been true for periods of overall de- spring. A summer dry spell in the Midwest can boost creasing prices-and there is plenty of this direction in summer prices, just as much as a near-perfect growing the most recent 10 years. Three negative storage re- season can depress them. For this reason there is a lot turn years are noted among the last 10. Those are the of variation from year-to-year in these weekly returns. 2009 crop as the great recession in 2009 caused (See the next article for some of those dynamics.) weak demand and lower corn prices. The second year of poor storage returns among the past ten was Those storing on-farm would also like to know the in the drought of 2012 when cash corn prices started odds of having a positive storage return in each of the at record highs near harvest and then generally periods. In Figure 2 we count the number of years in dropped through the storage season. The third major each of the three periods that there was a positive re- negative storage return year was the 2015 crop when turn to on-farm storage above interest cost. Looking at corn surpluses were growing and the reality of lower the 20 and 30 year periods, in roughly 60% to 80% of prices was setting in. As a general statement, corn the years there was a positive return to on-farm stor- prices were overall trending lower from the 2012 age during the peak return periods in February to early crop to the 2017 crop and thus setting the stage for -June. However the odds decrease somewhat into the the “lower than normal” period of speculative stor- summer. Why? As the spring approaches the new crop age returns shown here. situation begins to influence old crop prices. That information can increase or decrease old-crop prices.

18 | Page Purdue Agricultural Economics Report Therefore storage into the late- spring and summer is more risky depending on what happens to the new-crop growing conditions.

Returns to Speculative Com- mercial Corn Storage

What are the historic returns for storage at a commercial facility like the local grain elevator? In this case, the elevator is a licensed warehouse and has charges for their storage services. In this study there was a flat charge per bushel for storage until December 31 and then a monthly charge for each month of storage beginning Figure 3: Corn-Speculative Returns to Commercial Storage Above Interest and Elevator in January. The monthly charge Charges by Week ($/Bu.) was pro-rated by week. Of course over 30 years these storage rates have changed, but the study re- flects charges at the time. For the 2017 crop which represents the most recent year in the study, the charges were a $.18 per bushel flat charge until December 31 and then $.03 each month beginning in January, and pro-rated weekly. So, storage charges until the end of February were $.24 per bushel, and storage until the end of May were $.33 per bushel.

Estimated speculative storage returns above interest and storage charges are shown in Figure 3 for the three time periods. The best Figure 4: Corn-Historical Odds of a Positive Commercial Storage Return Above Interest time to price out of commercial and Elevator Charges by Week storage was in late-February and early-March. But also note that pricing in May and Historic returns above costs for corn storage have early-June gave speculative returns that were rough- been in the range of $.00 to $.10 per bushel on average ly equivalent, but likely with somewhat higher risk. for pricing at the historical optimal weeks. While this So, this shifts my preference a bit more in favor of seems small, it is a positive return above all costs. late-winter pricing, but others may decide to store Commercial storage facilities have substantial costs into the spring because of their personal situation or and do protect the quality of the grain for their storage because of their price outlook. customers. Those customers often have other im-

19 | Page Purdue Agricultural Economics Report portant motivations for storing corn such as rolling Over the long run periods representing the last 20 and income tax liabilities from the harvest year into the 30 years, estimated returns to cover the ownership and next tax year. operating costs of on-farm storage averaged $.25 to $.40 per bushel per year if one priced during the near Another important observation is to recognize how optimum weeks. sharply storage returns drop into the summer for commercial storage. The reason is three fold: cash There were two pricing windows for on-farm storage prices tend to drop; storage charges keep piling up; returns that stood out as averages across these multi- and interest costs continue to grow as well. year periods. The first was in late February and early March, but the highest returns came from pricing in Figure 4 shows that the historic odds of a positive May and early-June. return to storage have been about 50% for the longer run periods for the optimum pricing weeks. Or, in Returns for commercially stored corn averaged $.00 to the past 20 or 30 years, about 50% of the years had $.10 per bushel per year over the longer time periods positive commercial storage returns as calculated in for corn priced in the near optimal time windows. Re- this study in the optimal pricing weeks. member that commercial returns also subtracted the storage fees charged by the elevator as well as interest costs.

The near optimal windows for commercially stored corn were in late February and early-March or in May and early-June. But in contrast to on-farm storage, these two windows were roughly equivalent for commercial storage while May and early-June was superi- or for on-farm storage.

Another important observation from this historical record is that storage returns on average across these years tended to drop sharply after early-June with a Implications for Storage and Pricing Decisions tendency to fall further as the summer progressed. This was true for both on-farm and especially com- Does corn storage pay? How much? When is the mercial storage. This is driven by the average seasonal best time to price corn that is in storage? Are the cash price pattern in which summer cash corn prices conclusions different for on-farm stored corn com- tend to fall as the new crop develops. pared to corn stored at an elevator? These are some of the key questions that producers who store corn Returns calculated in this manner are called specula- may have. tive returns to storage. This is because one is mixing storage returns with speculation on price changes. This study attempts to shed light on these questions by looking at what has happened to Indiana corn Corn storage returns were lower in the most recent 10 storage returns in the past 10, 20, and 30 year time year period, but this is likely due to the unique period periods. The way these returns are calculated is out- of years as explained in the article. lined and those methods are important to the results. Interest costs were subtracted for both on-farm and Finally, these are results from history and that does commercial storage. Commercial storage fees were not mean the results will be the same in the future. also subtracted from commercial storage returns. There is much variation from year to year and this

20 | Page Purdue Agricultural Economics Report means those making storage and pricing decisions ic factors that impact their family or business. Cash will want to consider at least three factors in their flow needs and income tax management would be two decisions: the overall storage situation in each year; examples of how family or business needs often im- the price outlook in each year; and personal econom- pact storage and pricing decisions.

A CLOSER LOOK AT RECENT VARIABILITY IN ON-FARM CORN STORAGE RETURNS

CHRIS HURT, PROFESSOR OF AGRICULTURAL ECONOMICS

The corn and soybeans storage returns articles ex- weekly returns for the year. The three bad years to amine long run averages. These can be somewhat store corn in this period for speculative storage were misleading when there is a lot of variation from year the crops harvested in 2009, the 2012 drought and the to year. For this reason we are providing a peek at crop harvested in 2015. The average return for storing the weekly speculative on-farm corn returns data for the 2012 drought crop was a negative $.81 per bushel the last ten years. as an example.

One reason returns to speculative on-farm corn stor- In addition, the week of each year that was optimal for age are often highly variable is because one is mix- pricing is shown as a yellow shaded cell along with ing the returns to storage with returns to speculation the returns per bushel above the harvest price and in- on cash corn prices. Yet, it is the most common terest costs for that week. For these years there was a strategy among farmers and that is to put corn in the dominance for the optimum pricing week to be in bin at harvest and hope prices rise through the stor- May through the first two weeks of June with six of age season. the ten years having peak returns in that period, but which specific week varied. There are ways to separate out the returns to storage from returns to speculation. For example if a farmer What do these speculative storage returns look like for puts corn in the bin at a cash harvest value of $3.50 the 2018 corn crop? Those results have been added on a bushel and stores that until May when a huge the right hand side for results available at publication South American drought causes overall prices to time. So far the best storage returns for the 2018 corn rise to $5.50 they might say, “storage really paid crop were back in the second week of December this year.” In reality it was their speculation for (+$.27). Cash corn prices eroded in the early spring higher prices that really paid. We know this because with continued trade conflicts, higher corn stocks, and they could have earned much of the $2 increase by weak demand. Wet weather and delayed planting in selling the grain at harvest and replacing with fu- May 2019 began recovery in cash corn prices and thus tures. began to elevate speculative storage returns.

Table 1 shows the weekly returns to speculative on- One unique year can have a big influence on the long- farm corn storage above interest costs as outlined in er run averages. As an example look at the 2010/2011 the previous article. The marketing years are shown marketing year. This was the year nearing the final on the top row of the table. Numbers in red are neg- corn demand surge of the biofuels boom and the ative returns for that week. It may be a surprise to world economy recovered from the 2009 global reces- see how many of the weeks had a negative return. sion. As a result corn prices surged upward. Much At the bottom of the table is the average of the higher corn prices into the summer of 2011 drove the

21 | Page Purdue Agricultural Economics Report storage returns to reach $2.30 per bushel by June. ten year average. Will a similar unique year occur in This one unique year can have a large influence on a the next ten???

Table 1: Estimated Returns to Speculative On-Farm Storage by Week

22 | Page Purdue Agricultural Economics Report

SOYBEAN STORAGE RETURNS: IMPLICATIONS FOR STORAGE AND PRICING DECISIONS

CHRIS HURT, PROFESSOR OF AGRICULTURAL ECONOMICS

Soybean storage returns are examined in this article. the following May a South American drought causes The method of measuring those returns is similar to prices to rise to $12.00 most would declare this to be a corn. Please read the corn storage return article in high return to storage. In reality most of this high re- this publication for that information. One difference turn was due to prices being driven up by the drought. is that the harvest price for soybeans was assumed to As a price speculator, the farmer would receive this be the cash prices in the first two weeks of October, higher value, but the biggest part of the gain was due while the corn harvest price was assumed to be the to price speculation. last two weeks of October. Strong Speculative Soybean Storage Returns The weekly cash prices used were from a central In- diana elevator that loaded unit-trains. While both Our historical record suggest that those who stored corn and soybean data is from central Indiana, it is soybeans at harvest and then priced them later at the likely that the overall conclusions would hold for a cash bid have had strong positive returns on average broader geographic area including central and north- over the periods represented as the last 10 years, the ern Illinois, Indiana, Ohio and southern Michigan in last 20 years, and the last 30 years. the Eastern Corn Belt. Ohio and Illinois River markets may have some differences in patterns due to Returns above interest costs for on-farm storage for their unique shipping seasons. these three time periods are shown in Figure 1. Farm- ers and landlords who store soybeans are interested in As a brief summary, it is assumed the grain is placed knowing what weeks of the marketing year were best in storage at harvest time. The question then is, “do to be pricing in the past. That was late-April-May and cash price bids move above the harvest price during early-June. All three time periods exhibited this spring the storage season by enough to cover interest costs pricing preference. We also observe in Figure 1 that for on-farm storage?” For commercial storage the the returns to speculative on-farm storage tended to question is, “do cash price bids move above the har- rise consistently from harvest until the following vest price by enough to cover interest costs and com- spring on average. mercial storage charges?” You may also note that the 30 year time period which For on-farm storage, these results can be viewed as covers the crop harvested in 1988 to 2017 had lower an estimate of the returns per bushel to cover the overall returns to on-farm storage than the nearest 10 ownership and operating costs of on-farm storage. and nearest 20 year periods. This is due to some of the unique events for the crops harvested in 1988 to 1997. While putting soybeans in the bin at harvest and then That starts with the 1988 drought, and drought years pricing later is the most common farmer marketing generally have high prices at harvest with cash bids strategy we call these speculative returns to storage. dropping throughout the storage season. In addition This is because returns measured this way are mix- after 1995 the Asian financial crisis resulted in gener- ing the returns to storage and returns to speculating ally falling soybeans prices. Again it is hard to get a on the price. As an example, if one stores soybeans positive speculative return to storage when overall at harvest with a value of $9.00 per bushel, and by prices are generally going down.

23 | Page Purdue Agricultural Economics Report How much return per bushel was there for on-farm storage? The returns calculated in this manner can be viewed as an estimate of the returns above interest costs to cover the ownership and operating costs of on-farm storage. That estimate suggest the returns have been $.80 to $1.30 per bushel per year on average over the three time periods for beans priced during the optimum historic time periods in the spring.

Finally, as with corn the potential penalty for waiting to price soybeans into the following summer has been large on average in the past.

Figure 2 shows the historic odds of a Figure 1: Soybeans-Speculative Returns to On-Farm Storage Above Interest Cost positive storage return above interest by Week ($/Bu.) costs for on-farm storage. That reached 70% to 90% of the years by the spring for each of the periods. Results for speculative returns to commercial soybean storage are shown in Figure 3. Here, both interest costs and the commercial storage charges are subtracted from returns. This historical record shows that spring pricing was the most favora- ble on average over these periods and that speculative storage returns above interest and commercial storage charges averaged $.60 to $1.00 a bushel per year for the optimum spring pricing. The historical odds of a positive storage return to commercial storage were about 60% to 80% of the years Figure 2: Soybeans-Historical Odds of a Positive On-Farm Storage Return Above in each period for pricing in the Interest Cost by Week spring as seen in Figure 4. Summary Thoughts for Storage Decision Makers We call this speculative storage returns because it mixes the returns to storage and returns to speculat- Returns to speculative soybean storage have been ing on higher prices. The strong returns are likely strong in Indiana over the past decades on average as related to the huge growth of Chinese usage in the measured by this methodology. Those were $.80 to past 25 years. In addition, as the South American $1.30 per bushel for on-farm storage as an estimated crop has now become larger than the U.S. crop, return to cover the ownership and costs of operating growing seasons with reduced yields there have en- on-farm storage. Commercial storage returns aver- abled U.S. spring bean prices to rally by several dol- aged $.60 to $1.00 a bushel above all estimated costs.

24 | Page Purdue Agricultural Economics Report lars per bushel. These years have been very influential in the results in this study. While this study helps identify timing of pricing down to the week on average, there is a con- siderable amount of variation from year to year. This means there is value in learning about storage returns and in consider- ing the price outlook when making storage and pricing decisions. Farmers and landlords who store soybeans can start their storage and pricing strategies based upon these historic guidelines, but since each year can be different from the long term norm it is a good idea to make some potential Figure 3: Soybeans-Speculative Returns to Commercial Storage Above Interest and adjustments based on three factors: the storage situation for Elevator Charges by Week ($/Bu.) each year; the current price outlook; and for the particular economic situation of your business like cash flow needs and income tax management. One filter that has meaningful impacts on these results is to consider not storing in years when production is very low. Low production years, like the 2012 drought, have a strong tendency toward high prices at harvest with declining prices through the storage season. Mar- kets generally send price signals in these years not to store. These signals are likely to be in both the futures market and in the grain buyer’s cash bids. In the futures markets the harvest fu- Figure 4: Soybeans-Historical Odds of a Positive Commercial Storage Return Above tures (November for soybeans) Interest and Elevator Charges by Week will be higher priced than the futures during the storage season like the following same results will apply to the future. This means March-May-July futures (an inverted futures mar- you need to stay aware of economic forces that are ket). Secondly in the cash market, the grain bids different from year to year in making storage and may be higher for harvest delivery than they are for pricing decisions. One current example is the unusu- delivery through the winter and spring. al use of tariffs by the U.S. in 2018 and 2019. Finally, the results in this study are historical, and we all know that history is not an assurance that the

25 | Page Purdue Agricultural Economics Report

______

PURDUE UNIVERSITY ______

It is the policy of Purdue University that all persons have equal opportunity and access to its educational programs, services, activities, and facilities without regard to race, religion, color, sex, age, national origin or ancestry, marital status, parental status, sexual orientation, disability or status as a veteran.

Purdue University is an Affirmative Action institution. This material may be available in alternative formats.

CONTRIBUTORS

26 | Page